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Renamed variables and added debug log (#1537)

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* add debug logs

* renamed variables

* renamed TAGs, added flow status logging

* .

* .

Co-authored-by: CaCO3 <caco@ruinelli.ch>
This commit is contained in:
CaCO3
2022-12-10 20:39:43 +01:00
committed by GitHub
parent ba08b85225
commit 9d5846d0ce
11 changed files with 63 additions and 50 deletions
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80
code/components/jomjol_flowcontroll/ClassFlowCNNGeneral.cpp
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@@ -620,19 +620,22 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
}
tflite->MakeAllocate();
for (int _ana = 0; _ana < GENERAL.size(); ++_ana)
for (int n = 0; n < GENERAL.size(); ++n) // For each NUMBER
{
for (int i = 0; i < GENERAL[_ana]->ROI.size(); ++i)
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "Processing Number '" + GENERAL[n]->name + "'");
for (int roi = 0; roi < GENERAL[n]->ROI.size(); ++roi) // For each ROI
{
ESP_LOGD(TAG, "General %d - TfLite", i);
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "ROI #" + std::to_string(roi) + " - TfLite");
//ESP_LOGD(TAG, "General %d - TfLite", i);
switch (CNNType) {
case Analogue:
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "CNN Type: Analogue");
{
float f1, f2;
f1 = 0; f2 = 0;
tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);
tflite->LoadInputImageBasis(GENERAL[n]->ROI[roi]->image);
tflite->Invoke();
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "Nach Invoke");
@@ -640,39 +643,41 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
f2 = tflite->GetOutputValue(1);
float result = fmod(atan2(f1, f2) / (M_PI * 2) + 2, 1);
if(GENERAL[_ana]->ROI[i]->CCW)
GENERAL[_ana]->ROI[i]->result_float = 10 - (result * 10);
if(GENERAL[n]->ROI[roi]->CCW)
GENERAL[n]->ROI[roi]->result_float = 10 - (result * 10);
else
GENERAL[_ana]->ROI[i]->result_float = result * 10;
GENERAL[n]->ROI[roi]->result_float = result * 10;
ESP_LOGD(TAG, "Result General(Analog)%i - CCW: %d - %f", i, GENERAL[_ana]->ROI[i]->CCW, GENERAL[_ana]->ROI[i]->result_float);
ESP_LOGD(TAG, "Result General(Analog)%i - CCW: %d - %f", roi, GENERAL[n]->ROI[roi]->CCW, GENERAL[n]->ROI[roi]->result_float);
if (isLogImage)
LogImage(logPath, GENERAL[_ana]->ROI[i]->name, &GENERAL[_ana]->ROI[i]->result_float, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
LogImage(logPath, GENERAL[n]->ROI[roi]->name, &GENERAL[n]->ROI[roi]->result_float, NULL, time, GENERAL[n]->ROI[roi]->image_org);
} break;
case Digital:
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "CNN Type: Digital");
{
GENERAL[_ana]->ROI[i]->result_klasse = 0;
GENERAL[_ana]->ROI[i]->result_klasse = tflite->GetClassFromImageBasis(GENERAL[_ana]->ROI[i]->image);
ESP_LOGD(TAG, "Result General(Digit)%i: %d", i, GENERAL[_ana]->ROI[i]->result_klasse);
GENERAL[n]->ROI[roi]->result_klasse = 0;
GENERAL[n]->ROI[roi]->result_klasse = tflite->GetClassFromImageBasis(GENERAL[n]->ROI[roi]->image);
ESP_LOGD(TAG, "Result General(Digit)%i: %d", roi, GENERAL[n]->ROI[roi]->result_klasse);
if (isLogImage)
{
string _imagename = GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name;
string _imagename = GENERAL[n]->name + "_" + GENERAL[n]->ROI[roi]->name;
if (isLogImageSelect)
{
if (LogImageSelect.find(GENERAL[_ana]->ROI[i]->name) != std::string::npos)
LogImage(logPath, _imagename, NULL, &GENERAL[_ana]->ROI[i]->result_klasse, time, GENERAL[_ana]->ROI[i]->image_org);
if (LogImageSelect.find(GENERAL[n]->ROI[roi]->name) != std::string::npos)
LogImage(logPath, _imagename, NULL, &GENERAL[n]->ROI[roi]->result_klasse, time, GENERAL[n]->ROI[roi]->image_org);
}
else
{
LogImage(logPath, _imagename, NULL, &GENERAL[_ana]->ROI[i]->result_klasse, time, GENERAL[_ana]->ROI[i]->image_org);
LogImage(logPath, _imagename, NULL, &GENERAL[n]->ROI[roi]->result_klasse, time, GENERAL[n]->ROI[roi]->image_org);
}
}
} break;
/*
case DigitalHyprid:
{
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "CNN Type: DigitalHyprid");
int _num, _nachkomma;
tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);
@@ -713,6 +718,7 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
/*
case DigitalHyprid10:
{
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "CNN Type: DigitalHyprid10");
int _num, _nachkomma;
tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);
@@ -750,12 +756,13 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
case DoubleHyprid10:
{
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "CNN Type: DoubleHyprid10");
int _num, _numplus, _numminus;
float _val, _valplus, _valminus;
float _fit;
float _result_save_file;
tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);
tflite->LoadInputImageBasis(GENERAL[n]->ROI[roi]->image);
tflite->Invoke();
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "Nach Invoke");
@@ -795,7 +802,7 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
if (_fit < CNNGoodThreshold)
{
GENERAL[_ana]->ROI[i]->isReject = true;
GENERAL[n]->ROI[roi]->isReject = true;
result = -1;
_result_save_file+= 100; // Für den Fall, dass fit nicht ausreichend, soll trotzdem das Ergebnis mit "-10x.y" abgespeichert werden.
string zw = "Value Rejected due to Threshold (Fit: " + to_string(_fit) + "Threshold: " + to_string(CNNGoodThreshold) + ")";
@@ -803,24 +810,24 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
}
else
{
GENERAL[_ana]->ROI[i]->isReject = false;
GENERAL[n]->ROI[roi]->isReject = false;
}
GENERAL[_ana]->ROI[i]->result_float = result;
ESP_LOGD(TAG, "Result General(Analog)%i: %f", i, GENERAL[_ana]->ROI[i]->result_float);
GENERAL[n]->ROI[roi]->result_float = result;
ESP_LOGD(TAG, "Result General(Analog)%i: %f", roi, GENERAL[n]->ROI[roi]->result_float);
if (isLogImage)
{
string _imagename = GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name;
string _imagename = GENERAL[n]->name + "_" + GENERAL[n]->ROI[roi]->name;
if (isLogImageSelect)
{
if (LogImageSelect.find(GENERAL[_ana]->ROI[i]->name) != std::string::npos)
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
if (LogImageSelect.find(GENERAL[n]->ROI[roi]->name) != std::string::npos)
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[n]->ROI[roi]->image_org);
}
else
{
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[n]->ROI[roi]->image_org);
}
}
}
@@ -828,37 +835,38 @@ bool ClassFlowCNNGeneral::doNeuralNetwork(string time)
case Digital100:
case Analogue100:
{
LogFile.WriteToFile(ESP_LOG_DEBUG, TAG, "CNN Type: Digital100 or Analogue100");
int _num;
float _result_save_file;
tflite->LoadInputImageBasis(GENERAL[_ana]->ROI[i]->image);
tflite->LoadInputImageBasis(GENERAL[n]->ROI[roi]->image);
tflite->Invoke();
_num = tflite->GetOutClassification();
if(GENERAL[_ana]->ROI[i]->CCW)
GENERAL[_ana]->ROI[i]->result_float = 10 - ((float)_num / 10.0);
if(GENERAL[n]->ROI[roi]->CCW)
GENERAL[n]->ROI[roi]->result_float = 10 - ((float)_num / 10.0);
else
GENERAL[_ana]->ROI[i]->result_float = (float)_num / 10.0;
GENERAL[n]->ROI[roi]->result_float = (float)_num / 10.0;
_result_save_file = GENERAL[_ana]->ROI[i]->result_float;
_result_save_file = GENERAL[n]->ROI[roi]->result_float;
GENERAL[_ana]->ROI[i]->isReject = false;
GENERAL[n]->ROI[roi]->isReject = false;
ESP_LOGD(TAG, "Result General(Analog)%i - CCW: %d - %f", i, GENERAL[_ana]->ROI[i]->CCW, GENERAL[_ana]->ROI[i]->result_float);
ESP_LOGD(TAG, "Result General(Analog)%i - CCW: %d - %f", roi, GENERAL[n]->ROI[roi]->CCW, GENERAL[n]->ROI[roi]->result_float);
if (isLogImage)
{
string _imagename = GENERAL[_ana]->name + "_" + GENERAL[_ana]->ROI[i]->name;
string _imagename = GENERAL[n]->name + "_" + GENERAL[n]->ROI[roi]->name;
if (isLogImageSelect)
{
if (LogImageSelect.find(GENERAL[_ana]->ROI[i]->name) != std::string::npos)
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
if (LogImageSelect.find(GENERAL[n]->ROI[roi]->name) != std::string::npos)
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[n]->ROI[roi]->image_org);
}
else
{
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[_ana]->ROI[i]->image_org);
LogImage(logPath, _imagename, &_result_save_file, NULL, time, GENERAL[n]->ROI[roi]->image_org);
}
}